Farek Lazhar

14 papers Journal 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A dynamic hybrid attention-based autoencoder model with adaptive contextual attention for grammatical error correction. Int. J. Mach. Learn. Cybern. Farek Lazhar, Amira Benaidja
2026	J	`jnl`	A randomized block-based SVD image watermarking technique for IoT applications. Multim. Tools Appl. Amira Benaidja, Farek Lazhar
2026	J	`jnl`	Transformer-vae for contextual anomaly detection in text. Int. J. Mach. Learn. Cybern. Farek Lazhar, Amira Benaidja
2025	J	`jnl`	An adaptive binary particle swarm optimization algorithm with filtration and local search for feature selection in text classification. Memetic Comput. Farek Lazhar, Amira Benaidja
2025	J	`jnl`	An optimal feature selection method for text classification through redundancy and synergy analysis. Multim. Tools Appl. Farek Lazhar, Amira Benaidja
2025	J	`jnl`	Hybrid Accurate Localization Approach for Dense and Highly Mobile Vehicular Networks. Int. J. Commun. Syst. Amira Benaidja, Farek Lazhar
2024	J	`jnl`	A hybrid feature selection method for text classification using a feature-correlation-based genetic algorithm. Soft Comput. Farek Lazhar, Amira Benaidja
2024	J	`jnl`	A non-redundant feature selection method for text categorization based on term co-occurrence frequency and mutual information. Multim. Tools Appl. Farek Lazhar, Amira Benaidja
2024	J	`jnl`	Feature redundancy removal for text classification using correlated feature subsets. Comput. Intell. Farek Lazhar, Amira Benaidja
2024	J	`jnl`	Semantic similarity-aware feature selection and redundancy removal for text classification using joint mutual information. Knowl. Inf. Syst. Farek Lazhar, Amira Benaidja
2019	J	`jnl`	Fuzzy clustering-based semi-supervised approach for outlier detection in big text data. Prog. Artif. Intell. Farek Lazhar
2019	J	`jnl`	Implicit feature identification for opinion mining. Int. J. Bus. Inf. Syst. Farek Lazhar
2018	J	`jnl`	Mining hidden opinions from objective sentences. Int. J. Data Min. Model. Manag. Farek Lazhar
2016	J	`jnl`	Mining explicit and implicit opinions from reviews. Int. J. Data Min. Model. Manag. Farek Lazhar, Yamina Tlili Guiyassa

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.